Infrared systems are used in missile targeting systems for automatically identifying and selecting targets from background clutter, which can include weather conditions, such as fog, flares, jamming devices and other countermeasures. Typically, such a system employs thresholding to make such identification and selection. For example, the system might use a threshold in conjunction with a polarity indicator to separate the bright or dark pixels belonging to the target from the remainder of the image. Alternatively, the system may use multiple thresholds, with the target pixels having grey levels that fall between or outside the bands specified by the threshold values. These systems then calculate the target centroid using the identified target pixels weighted by either a binary weight or the difference between the intensity of the pixel and the discrete thresholds.
An example of a system that employs multiple thresholds is described in U.S. Pat. No. 5,878,163. Unfortunately, the system described therein has been found to suffer from certain drawbacks.
First, the system has difficulty modeling a complex target in which pixels representing the target have more than one range of intensities in common with the background. Second, the selection of the appropriate thresholds can be computationally expensive in systems having a large number of grey shades. Third, in the case where the target has very hot regions (e.g., a burning object), the thresholds generated or calculated by the system may jump erratically, resulting in a problem with the tracker commonly known as “break lock.”
Accordingly, it would be advantageous to have a centroid tracker that does not use discrete thresholds for distinguishing target pixels from background pixels. It would also be advantageous to have a centroid tracker, which could reduce the computational expense necessary for tracking systems employing a large number of grey shades.